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您的检索式：作者名="Sensen Chu"
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| 1 | Rice OsUBR7 modulates plant height by regulating histone H2B monoubiquitination and cell proliferation显示文摘Plant height is an important agronomic trait for lodging resistance and yield.Here,we report a new plantheight-related gene,OsUBR7 in rice(Oryza sativa L.);knockout of OsUBR7 caused fewer cells in internodes,resulting in a semi-dwarf phenotype.OsUBR7 encodes a putative E3 ligase containing a plant homeodomain finger and a ubiquitin protein ligase E3 component N-recognin 7(UBR7)domain.OsUBR7 interacts with histones and monoubiquitinates H2B(H2Bub1)at lysine148 in coordination with the E2 conjugase OsUBC18.OsUBR7 mediates H2Bub1 at a number of chromatin loci for the normal expression of target genes,including cell-cycle-related and pleiotropic genes,consistent with the observation that cell-cycle progression was suppressed in the osubr7 mutant owing to reductions in H2Bub1 and expression levels at these loci.The genetic divergence of OsUBR7 alleles among japonica and indica cultivars affects their transcriptional activity,and these alleles may have undergone selection during rice domestication.Overall,our results reveal a novel mechanism that mediates H2Bub1 in plants,and UBR7 orthologs could be utilized as an untapped epigenetic resource for crop improvement. | Yangyi Zheng Sensen Zhang Yanqiu Luo Fuquan Li Jiantao Tan Bin Wang Zhe Zhao Huifang Lin Tingting Zhang Jianhong Liu Xupeng Liu Jingxin Guo Xianrong Xie Letian Chen Yao-Guang Liu Zhizhan Chu | 2022 | Plant Communications2022，3，6： | 0 |
| 2 | Shallow water bathymetry based on a back propagation neural network and ensemble learning using multispectral satellite imagery显示文摘The back propagation(BP)neural network method is widely used in bathymetry based on multispectral satellite imagery.However,the classical BP neural network method faces a potential problem because it easily falls into a local minimum,leading to model training failure.This study confirmed that the local minimum problem of the BP neural network method exists in the bathymetry field and cannot be ignored.Furthermore,to solve the local minimum problem of the BP neural network method,a bathymetry method based on a BP neural network and ensemble learning(BPEL)is proposed.First,the remote sensing imagery and training sample were used as input datasets,and the BP method was used as the base learner to produce multiple water depth inversion results.Then,a new ensemble strategy,namely the minimum outlying degree method,was proposed and used to integrate the water depth inversion results.Finally,an ensemble bathymetric map was acquired.Anda Reef,northeastern Jiuzhang Atoll,and Pingtan coastal zone were selected as test cases to validate the proposed method.Compared with the BP neural network method,the root-mean-square error and the average relative error of the BPEL method can reduce by 0.65–2.84 m and 16%–46%in the three test cases at most.The results showed that the proposed BPEL method could solve the local minimum problem of the BP neural network method and obtain highly robust and accurate bathymetric maps. | Sensen Chu Liang Cheng Jian Cheng Xuedong Zhang Jie Zhang Jiabing Chen Jinming Liu | 2023 | Acta Oceanologica Sinica2023，42，5： | 0 |
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